Ordinamento stocastico basato sulle permutazioni utilizzando confronti a coppie

The topic of this work concerns nonparametric permutation-based methods aiming to find a ranking (stochastic ordering) of a given set of groups (populations), gathering together information from multiple variables under more than one experimental designs. The problem of ranking populations arises in several fields of science from the need of comparing G>2 given groups or treatments when the main goal is to find an order while taking into account several aspects. As it can be imagined, this problem is not only of theoretical interest but it also has a recognised relevance in several fields, such as industrial experiments or behavioural sciences, and this is reflected by the vast literature on the topic, although sometimes the problem is associated with different keywords such as: "stochastic ordering", "ranking", "construction of composite indices" etc., or even "ranking probabilities" outside of the strictly-speaking statistical literature. The properties of the proposed method are empirically evaluated by means of an extensive simulation study, where several aspects of interest are let to vary within a reasonable practical range. These aspects comprise: sample size, number of variables, number of groups, and distribution of noise/error. The flexibility of the approach lies mainly in the several available choices for the test-statistic and in the different types of experimental design that can be analysed. This render the method able to be tailored to the specific problem and the to nature of the data at hand. To perform the analyses an R package called SOUP (Stochastic Ordering Using Permutations) has been written and it is available on CRAN

A prognostic model integrating PET-derived metrics and image texture analyses with clinical risk factors from GOYA

Image texture analysis (radiomics) uses radiographic images to quantify characteristics that may identify tumour heterogeneity and associated patient outcomes. Using fluoro‐deoxy‐glucose positron emission tomography/computed tomography (FDG‐PET/CT)‐derived data, including quantitative metrics, image texture analysis and other clinical risk factors, we aimed to develop a prognostic model that predicts survival in patients with previously untreated diffuse large B‐cell lymphoma (DLBCL) from GOYA (NCT01287741). Image texture features and clinical risk factors were combined into a random forest model and compared with the international prognostic index (IPI) for DLBCL based on progression‐free survival (PFS) and overall survival (OS) predictions. Baseline FDG‐PET scans were available for 1263 patients, 832 patients of these were cell‐of‐origin (COO)‐evaluable. Patients were stratified by IPI or radiomics features plus clinical risk factors into low‐, intermediate‐ and high‐risk groups. The random forest model with COO subgroups identified a clearer high‐risk population (45% 2‐year PFS [95% confidence interval (CI) 40%–52%]; 65% 2‐year OS [95% CI 59%–71%]) than the IPI (58% 2‐year PFS [95% CI 50%–67%]; 69% 2‐year OS [95% CI 62%–77%]). This study confirms that standard clinical risk factors can be combined with PET‐derived image texture features to provide an improved prognostic model predicting survival in untreated DLBCL

Total metabolic tumor volume as a survival predictor for patients with diffuse large B-cell lymphoma in the GOYA study

This retrospective analysis of the phase III GOYA study investigated the prognostic value of baseline metabolic tumor volume parameters and maximum standardized uptake values for overall and progression-free survival (PFS) in treatment-naïve diffuse large B-cell lymphoma. Baseline total metabolic tumor volume (determined for tumors >1 mL using a threshold of 1.5 times the mean liver standardized uptake value +2 standard deviations), total lesion glycolysis, and maximum standardized uptake value positron emission tomography data were dichotomized based on receiver operating characteristic analysis and divided into quartiles by baseline population distribution. Of 1,418 enrolled patients, 1,305 had a baseline positron emission tomography scan with detectable lesions. Optimal cut-offs were 366 cm3 for total metabolic tumor volume and 3,004 g for total lesion glycolysis. High total metabolic tumor volume and total lesion glycolysis predicted poorer PFS, with associations retained after adjustment for baseline and disease characteristics (high total metabolic tumor volume hazard ratio: 1.71, 95% confidence interval [CI]: 1.352.18; total lesion glycolysis hazard ratio: 1.46; 95% CI: 1.15-1.86). Total metabolic tumor volume was prognostic for PFS in subgroups with International Prognostic Index scores 0-2 and 3-5, and those with different cell-of-origin subtypes. Maximum standardized uptake value had no prognostic value in this setting. High total metabolic tumor volume associated with high International Prognostic Index or non-germinal center B-cell classification identified the highest-risk cohort for unfavorable prognosis. In conclusion, baseline total metabolic tumor volume and total lesion glycolysis are independent predictors of PFS in patients with diffuse large B-cell lymphoma after first-line immunochemotherapy

End-of-treatment PET/CT predicts PFS and OS in DLBCL after first-line treatment: results from GOYA

GOYA was a randomized phase 3 study comparing obinutuzumab plus cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP) vs standard-of-care rituximab plus CHOP in patients with previously untreated diffuse large B-cell lymphoma (DLBCL). This retrospective analysis of GOYA aimed to assess the association between progression-free survival (PFS) and overall survival (OS) with positron emission tomography (PET)-based complete response (CR) status. Overall, 1418 patients were randomly assigned to receive 8 21-day cycles of obinutuzumab (n 5 706) or rituximab (n 5 712) plus 6 or 8 cycles of CHOP. Patients received a mandatory fluoro-2-deoxy-D-glucose-PET/computed tomography scan at baseline and end of treatment. After a median follow-up of 29 months, the numbers of independent review committee-assessed PFS and OS events in the entire cohort were 416 (29.3%) and 252 (17.8%), respectively. End-of-treatment PET CR was highly prognostic for PFS and OS according to Lugano 2014 criteria (PFS: hazard ratio [HR], 0.26; 95% confidence interval [CI], 0.19-0.38; P , .0001; OS: HR, 0.12; 95% CI, 0.08-0.17; P , .0001), irrespective of international prognostic index score and cell of origin. In conclusion, the results from this prospectively acquired large cohort corroborated previously published data from smaller sample sizes showing that end-of-treatment PET CR is an independent predictor of PFS and OS and a promising prognostic marker in DLBCL. Long-term survival analysis confirmed the robustness of these data over time. Additional meta-analyses including other prospective studies are necessary to support the substitution of PET CR for PFS as an effective and practical surrogate end point

Preoperative Fibrinogen-to-Albumin Ratio as Potential Predictor of Bladder Cancer: A Monocentric Retrospective Study

: Background and objective: Fibrinogen and albumin are two proteins widely used, singularly and in combination, in cancer patients as biomarkers of nutritional status, inflammation and disease prognosis. The aim of our study was to investigate the preoperative fibrinogen-to-albumin ratio (FAR) as a preoperative predictor of malignancy as well as advanced grade in patients with bladder cancer. Materials and Methods: A retrospective analysis of patients who underwent TURBT at our institution between 2017 and 2021 was conducted. FAR was obtained from preoperative venous blood samples performed within 30 days from scheduled surgery and was analyzed in relation to histopathological reports, as was the presence of malignancy. Statistical analysis was performed using a Kruskal−Wallis Test, and univariate and multivariate logistic regression analysis, assuming p < 0.05 to be statistically significant. Results: A total of 510 patients were included in the study (81% male, 19% female), with a mean age of 71.66 ± 11.64 years. The mean FAR was significantly higher in patients with low-grade and high-grade bladder cancer, with values of 80.71 ± 23.15 and 84.93 ± 29.96, respectively, compared to patients without cancer (75.50 ± 24.81) (p = 0.006). Univariate regression analysis reported FAR to be irrelevant when considered as a continuous variable (OR = 1.013, 95% CI = 1.004−1.022; p = 0.004), while when considered as a categorical variable, utilizing a cut-off set at 76, OR was 2.062 (95% CI = 1.378−3.084; p < 0.0001). Nevertheless, the data were not confirmed in the multivariate analysis. Conclusions: Elevated preoperative FAR is a potential predictor of malignancy as well as advanced grade in patients with bladder cancer. Further data are required to suggest a promising role of the fibrinogen-to-albumin ratio as a diagnostic biomarker for bladder tumors

A broken promise : microbiome differential abundance methods do not control the false discovery rate

High-throughput sequencing technologies allow easy characterization of the human microbiome, but the statistical methods to analyze microbiome data are still in their infancy. Differential abundance methods aim at detecting associations between the abundances of bacterial species and subject grouping factors. The results of such methods are important to identify the microbiome as a prognostic or diagnostic biomarker or to demonstrate efficacy of prodrug or antibiotic drugs. Because of a lack of benchmarking studies in the microbiome field, no consensus exists on the performance of the statistical methods. We have compared a large number of popular methods through extensive parametric and nonparametric simulation as well as real data shuffling algorithms. The results are consistent over the different approaches and all point to an alarming excess of false discoveries. This raises great doubts about the reliability of discoveries in past studies and imperils reproducibility of microbiome experiments. To further improve method benchmarking, we introduce a new simulation tool that allows to generate correlated count data following any univariate count distribution; the correlation structure may be inferred from real data. Most simulation studies discard the correlation between species, but our results indicate that this correlation can negatively affect the performance of statistical methods

Educating patients suffering from re-acutisation of chronic bronchitis. A pilot support project within Intermediate Care

&lt;p&gt;&lt;strong&gt;Background&lt;/strong&gt;: Chronic Obstructive Pulmonary Disease (COPD) represents one of the main causes of hospitalization, disability and mortality worldwide; it is predicted that by the year 2020 it will become the third leading cause of death and the fifth leading cause of disability in industrialized countries. An educational programme has been proposed to allow the COPD patient to prevent or to deal with a reacutisation.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods&lt;/strong&gt;: The project involved 50 patients with a diagnosis of moderate or severe COPD. The education program included information relating to disease process, proper use of medication, energy conservation methods, and the filling in of the Saint George’s Respiratory Questionnaire (SGRQ), the Zung Self-Rating Depression Scale (ZSDS) and the State Trait Anxiety Inventory (STAI). Sociodemographic factors, assessment of living arrangements, social and family conditions were also collected. One year later the same questionnaires and learning assessment tests were re-administered.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results&lt;/strong&gt;: The mean age of the participants was 69.7±10.4 years with a mean low income and a limited degree of education. Following the educational program, an improvement of quality of life emerged consequent to the awareness of all of the forms of support provided for the pathology and socio-economic conditions. The ability to manage their therapy and their activities of daily living have improved. The mean total score on SGRQ was 78.07±7.2 pre-program and 73.12±7.2 post-program; 52% of the patients are now within normal parameters compared to the initial 30% suffering from depression syndrome, furthermore the mean anxiety value decreased from 59.54 ± 8.6 to 54.54±7.8. The number of hospital admissions and the number of smokers were also halved.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion&lt;/strong&gt;: The improvements obtained after conducting all of the educational sessions are significant. The high value of the mean total score on SGRQ suggests overall poor health among patients affected by moderate/ severe COPD and according to other studies this population is inclined to anxiety and depression. The role of the social worker was very important because the explanation of the appropriate laws has lead to the recognition of their disability status and therefore access to established benefits. The decrease in hospitalization has brought about an economic benefit for the educational program but further studies should be carried out on more patients over longer periods of time.&lt;/p&gt